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Abstract Background Preliminary evidence suggests that people who inject drugs (PWID) may be at an increased risk of developing infective endocarditis (IE), hepatitis C virus (HCV) infection, and/or human immunodeficiency virus (HIV) infection from hydromorphone controlled-release formulation. The hypothesized mechanism is related to insolubility of the drug, which promotes reuse, leading to contamination of injecting equipment. However, this relationship has not been confirmed. We aimed to conduct a systematic review including adult PWID exposed to controlled-release hydromorphone and the risk of acquiring IE, HCV, and HIV. Methods We searched MEDLINE, EMBASE, and Evidence Based Medicine reviews from inception until September 2021. Following pilot testing, two reviewers conducted all screening of citations and full-text articles, as well as abstracted data, and appraised risk of bias using the Newcastle–Ottawa scale and Effective Practice and Organization of Care tool. Equity issues were examined using the PROGRESS-PLUS framework. Discrepancies were resolved consistently by a third reviewer. Meta-analysis was not feasible due to heterogeneity across the studies. Results After screening 3,231 citations from electronic databases, 722 citations from unpublished sources/reference scanning, and 626 full-text articles, five studies were included. Five were cohort studies, and one was a case–control study. The risk of bias varied across the studies. Two studies reported on gender, as well as other PROGRESS-PLUS criteria (race, housing, and employment). Three studies focused specifically on the controlled-release formulation of hydromorphone, whereas two studies focused on all formulations of hydromorphone. One retrospective cohort study found an association between controlled-release hydromorphone and IE, whereas a case–control study found no evidence of an association. One retrospective cohort study found an association between the number of hydromorphone controlled-release prescriptions and prevalence of HCV. None of the studies specifically reported on associations with HIV. Discussion Very few studies have examined the risk of IE, HCV, and HIV infection after exposure to controlled-release hydromorphone. Very low-quality and scant evidence suggests uncertainty around the risks of blood-borne infections, such as HCV and IE to PWID using this medication.

Objectives To identify ML tools in hospital settings and how they were implemented to inform decision-making for patient care through a scoping review. We investigated the following research questions: What ML interventions have been used to inform decision-making for patient care in hospital settings? What strategies have been used to implement these ML interventions?Design A scoping review was undertaken. MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Database of Systematic Reviews (CDSR) were searched from 2009 until June 2021. Two reviewers screened titles and abstracts, full-text articles, and charted data independently. Conflicts were resolved by another reviewer. Data were summarised descriptively using simple content analysis.Setting Hospital setting.Participant Any type of clinician caring for any type of patient.Intervention Machine learning tools used by clinicians to inform decision-making for patient care, such as AI-based computerised decision support systems or “‘model-based’” decision support systems.Primary and secondary outcome measures Patient and study characteristics, as well as intervention characteristics including the type of machine learning tool, implementation strategies, target population. Equity issues were examined with PROGRESS-PLUS criteria.Results After screening 17 386 citations and 3474 full-text articles, 20 unique studies and 1 companion report were included. The included articles totalled 82 656 patients and 915 clinicians. Seven studies reported gender and four studies reported PROGRESS-PLUS criteria (race, health insurance, rural/urban). Common implementation strategies for the tools were clinician reminders that integrated ML predictions (44.4%), facilitated relay of clinical information (17.8%) and staff education (15.6%). Common barriers to successful implementation of ML tools were time (11.1%) and reliability (11.1%), and common facilitators were time/efficiency (13.6%) and perceived usefulness (13.6%).Conclusions We found limited evidence related to the implementation of ML tools to assist clinicians with patient healthcare decisions in hospital settings. Future research should examine other approaches to integrating ML into hospital clinician decisions related to patient care, and report on PROGRESS-PLUS items.Funding Canadian Institutes of Health Research (CIHR) Foundation grant awarded to SES and the CIHR Strategy for Patient Oriented-Research Initiative (GSR-154442).Scoping review registration https://osf.io/e2mna.

Abstract Background As the population ages, older hospitalized patients are at increased risk for hospital-acquired morbidity. The Mobilization of Vulnerable Elders (MOVE) program is an evidence-informed early mobilization intervention that was previously evaluated in Ontario, Canada. The program was effective at improving mobilization rates and decreasing length of stay in academic hospitals. The aim of this study was to scale-up the program and conduct a replication study evaluating the impact of the evidence-informed mobilization intervention on various units in community hospitals within a different Canadian province. Methods The MOVE program was tailored to the local context at four community hospitals in Alberta, Canada. The study population was patients aged 65 years and older who were admitted to medicine, surgery, rehabilitation and intensive care units between July 2015 and July 2016. The primary outcome was patient mobilization measured by conducting visual audits twice a week, three times a day. The secondary outcomes included hospital length of stay obtained from hospital administrative data, and perceptions of the intervention assessed through a qualitative assessment. Using an interrupted time series design, the intervention was evaluated over three time periods (pre-intervention, during, and post-intervention). Results A total of 3601 patients [mean age 80.1 years (SD = 8.4 years)] were included in the overall analysis. There was a significant increase in mobilization at the end of the intervention period compared to pre-intervention, with 6% more patients out of bed (95% confidence interval (CI) 1, 11; p-value = 0.0173). A decreasing trend in median length of stay was observed, where patients on average stayed an estimated 3.59 fewer days (95%CI -15.06, 7.88) during the intervention compared to pre-intervention period. Conclusions MOVE is a low-cost, effective and adaptable intervention that improves mobilization in older hospitalized patients. This intervention has been replicated and scaled up across various units and hospital settings.

Abstract Background Bed rest for older hospitalized patients places them at risk for hospital-acquired morbidity. We previously evaluated an early mobilization intervention and found it to be effective at improving mobilization rates and decreasing length of stay on internal medicine units. The aim of this study was to conduct a replication study evaluating the impact of the evidence-informed mobilization intervention on surgery, psychiatry, medicine, and cardiology inpatient units. Methods A multi-component early mobilization intervention was tailored to the local context at seven hospitals in Ontario, Canada. The primary outcome was patient mobilization measured by conducting visual audits twice a week, three times a day. Secondary outcomes were hospital length of stay and discharge destination, which were obtained from hospital decision support data. The study population was patients aged 65 years and older who were admitted to surgery, psychiatry, medicine, and cardiology inpatient units between March and August 2014. Using an interrupted time series design, the intervention was evaluated over three time periods–pre-intervention, during, and post-intervention. Results A total of 3098 patients [mean age 78.46 years (SD 8.38)] were included in the overall analysis. There was a significant increase in mobility immediately after the intervention period compared to pre-intervention with a slope change of 1.91 (95% confidence interval [CI] 0.74–3.08, P-value = 0.0014). A decreasing trend in median length of stay was observed in the majority of the participating sites. Overall, a median length of stay of 26.24 days (95% CI 23.67–28.80) was observed pre-intervention compared to 23.81 days (95% CI 20.13–27.49) during the intervention and 24.69 days (95% CI 22.43–26.95) post-intervention. The overall decrease in median length of stay was associated with the increase in mobility across the sites. Conclusions MOVE increased mobilization and these results were replicated across surgery, psychiatry, medicine, and cardiology inpatient units.

Abstract Background In 2013, Health Quality Ontario introduced stroke quality-based procedures (QBPs) to promote use of evidence-based practices for patients with stroke in Ontario hospitals. The study purpose was to: (a) describe the knowledge translation (KT) interventions used to support stroke QBP implementation, (b) assess differences in the planned and reported KT interventions by region, and (c) explore determinants perceived to have affected outcomes. Methods A mixed methods approach was used to evaluate: activities, KT interventions, and determinants of stroke QBP implementation. In Phase 1, a document review of regional stroke network work plans was conducted to capture the types of KT activities planned at a regional level; these were mapped to the knowledge to action framework. In Phase 2, we surveyed Ontario hospital staff to identify the KT interventions used to support QBP implementation at an organizational level. Phase 3 involved qualitative interviews with staff to elucidate deeper understanding of survey findings. Results Of the 446 activities identified in the document review, the most common were ‘dissemination’ (24.2%; n = 108), ‘implementation’ (22.6%; n = 101), ‘implementation planning’ (15.0%; n = 67), and ‘knowledge tools’ (10.5%; n = 47). Based on survey data (n = 489), commonly reported KT interventions included: staff educational meetings (43.1%; n = 154), champions (41.5%; n = 148), and staff educational materials (40.6%; n = 145). Survey participants perceived stroke QBP implementation to be successful (median = 5/7; interquartile range = 4–6; range = 1–7; n = 335). Forty-four people (e.g., managers, senior leaders, regional stroke network representatives, and frontline staff) participated in interviews/focus groups. Perceived facilitators to QBP implementation included networks and collaborations with external organizations, leadership engagement, and hospital prioritization of stroke QBP. Perceived barriers included lack of funding, size of the hospital (i.e., too small), lack of resources (i.e., staff and time), and simultaneous implementation of other QBPs. Conclusions Information on the types of activities and KT interventions used to support stroke QBP implementation and the key determinants influencing uptake of stroke QBPs can be used to inform future activities including the development and evaluation of interventions to address barriers and leverage facilitators.